SDDNet: Real-Time Crack Segmentation

This article reports the development of a pure deep learning method for segmenting concrete cracks in images. The objectives are to achieve the real-time performance while effectively negating a wide range of various complex backgrounds and crack-like features. To achieve the goals, an original conv...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2020-09, Vol.67 (9), p.8016-8025
Main Authors: Choi, Wooram, Cha, Young-Jin
Format: Article
Language:English
Subjects:
Artificial neural networks
Computational efficiency
Computer architecture
Convolution
Crack segmentation
Damage detection
Decoding
deep learning (DL)
Feature extraction
Image segmentation
Machine learning
Modules
Real time
Real-time systems
separable convolution
structural health monitoring (SHM)
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